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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah Kursor Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi JURNAL EKONOMI DAN BISNIS AIRLANGGA EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Teknik Komputer AMIK BSI INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi InComTech: Jurnal Telekomunikasi dan Komputer JURNAL REKAYASA TEKNOLOGI INFORMASI KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Telematika Indonesian Journal of Applied Informatics Jurnal Sistem Cerdas JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Teknologi Informasi dan Terapan (J-TIT) Syntax Idea JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Aiti: Jurnal Teknologi Informasi Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia Journal Automation Computer Information System (JACIS) INTERNATIONAL JOURNAL OF EDUCATION, INFORMATION TECHNOLOGY, AND OTHERS Indonesian Community Journal Jurnal Algoritma Journal of Social Science J-Icon : Jurnal Komputer dan Informatika Journal of Computing Theories and Applications Asian Journal of Management, Entrepreneurship and Social Science JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komtika (Komputasi dan Informatika) Jurnal Abdi Rakyat
Rianto Rianto
Universitas Teknologi Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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Osteoporosis Detection Using a Combination of Recursive Feature Elimination and Naive Bayes Classifier with Rule-Based Chatbot Testing Sela, Enny Itje; Rianto, Rianto; Anggara, Afwan; Utami, Wahyu Sri
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.409

Abstract

Osteoporosis is a condition characterized by reduced bone mass and density, increasing the risk of fractures. Early detection relies on patient awareness and proactive health management. Despite advances in technology, patient independence and awareness remain critical for early diagnosis. A rule-based chatbot tool can assist by helping patients screen their bone health. The chatbot provides automated recommendations, offering an alternative to traditional hospital visits. This study presents a rule-based chatbot designed to detect osteoporosis, using Recursive Feature Elimination (RFE) combined with the Naïve Bayes Classifier (NBC). Machine learning is integrated to enhance the chatbot's ability to identify early signs of osteoporosis. The model’s performance is compared to other feature selection methods, such as Principal Component Analysis (PCA), and machine learning algorithms like Deep Learning, Support Vector Machine (SVM), and Logistic Regression. The dataset used includes public data sets for training and validation, as well as data from the Yogyakarta Health Office for predictions. Research phases include normalization, data encoding, feature selection, training, validation, and prediction. The chatbot implements text preprocessing techniques, such as tokenization, stop word removal, and feature extraction, alongside normalization and encoding of numeric data. The prediction stage determines if the patient has a positive or negative osteoporosis status. Validation results show the RFE-NBC model is particularly effective for osteoporosis detection, offering a balanced performance in identifying both positive and negative cases. Additionally, this model served as the foundation for creating a rule-based chatbot designed to detect osteoporosis. Based on the set of testing metrics using chatbot, the model demonstrates strong overall performance, with a good balance between identifying positive and negative instances.
Optimizing The User Interface of Waste Bank Application Using UCD and UEQ Prihatini, Retno; Rianto
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.83998

Abstract

Environmental cleanliness is an essential aspect of life to make a healthy and comfortable environment. In Indonesia, the volume of waste will reach 70 million tons by 2022, with around 24% or 16 million tons needing to be appropriately managed. Related to the significant waste growth, the Ministry of Environment has developed the Waste Bank initiative, a collaborative effort that aims to educate the public in sorting waste and raising awareness of the importance of wise waste management. The desire of the local environmental agency to connect with the community supports the researcher in developing the Waste Bank application. The application will implement an optimal User Interface (UI) and User Experience (UX) design. The User-Centered Design (UCD) method will be employed, supported by the User Experience Questionnaire (UEQ), and is used to design UI and UX for the Waste Bank mobile application. The application prototypes were tested and evaluated using UEQ. The first design achieved an average score but still required improvement. In contrast, the second design scored excellently in six aspects measured: attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty, with significant improvement. These results show that the UCD and UEQ methods are effective for developing UI/UX designs to meet user needs and can be applied in mobile application developments.
Analisis Kualitas Layanan Jaringan Wlan Berdasarkan Parameter Throughput, Delay, Jitter, dan Packet Loss di Universitas X Syafrudin, Teguh; Rianto, Rianto; Ujianto, EIH
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 8 (2025): JPTI - Agustus 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.887

Abstract

Penelitian ini bertujuan untuk mengevaluasi kualitas layanan jaringan WLAN di Universitas X menggunakan metode Quality of Service (QoS) yang melibatkan pengukuran parameter Throughput, Delay, Jitter, dan Packet Loss. Proses pengumpulan data melibatkan wawancara dengan karyawan IT, observasi langsung, serta pemanfaatan perangkat lunak seperti Wireshark. Hasil penelitian menunjukkan bahwa kualitas jaringan WLAN secara keseluruhan berada dalam kategori "sangat memuaskan" berdasarkan standar TIPHON. Namun, terdapat kelemahan pada Throughput jaringan lokal dan IP publik yang dikategorikan "kurang baik". Hal ini menandakan perlunya peningkatan kapasitas Throughput agar performa jaringan lebih optimal. Penelitian ini memberikan kontribusi signifikan terhadap pengembangan infrastruktur jaringan di lingkungan kampus. Dengan saran berbasis data yang dihasilkan, diharapkan layanan internet dapat ditingkatkan secara menyeluruh untuk mendukung aktivitas pembelajaran berbasis ICT.
Perbandingan Algoritma Support Vector Machine (SVM) dan Decision Tree untuk Sistem Rekomendasi Tempat Wisata Oktafiani, Rian; Rianto, Rianto
Jurnal Nasional Teknologi dan Sistem Informasi Vol 9 No 2 (2023): Agustus 2023
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v9i2.2023.113-121

Abstract

Industri pariwisata Indonesia berkembang dari tahun ke tahun. Daerah Istimewa Yogyakarta merupakan salah satu provinsi yang memiliki banyak destinasi wisata. Pertumbuhan internet dan teknologi informasi juga menjadi faktor dalam industri pariwisata Indonesia. Dengan adanya informasi mengenai pariwisata di internet, dapat memudahkan wisatawan untuk mencari informasi. Namun, karena jumlah informasi yang sangat banyak akan membuat wisatawan kebingungan untuk menentukan tujuan wisata. Selain itu, wisata lokal memiliki potensi yang cukup tinggi untuk membantu perekonomian daerah, namun saat ini belum dieksplorasi secara maksimal. Sistem rekomendasi dan kemampuan klasifikasi tempat wisata diperlukan untuk memberikan akurasi rekomendasi yang baik. Untuk menentukan jumlah fitur yang paling menguntungkan untuk klasifikasi lokasi wisata, Teknik Principal Component Analysis (PCA) digunakan dalam penelitian ini untuk membandingkan metodologi Support Vector Machine (SVM) dan Decision Tree (DT). Hasilnya menunjukkan bahwa, dengan nilai akurasi 98.97% penerapan PCA dengan nilai n=5 dan berada pada perbandingan Split Data 75% : 25%, pendekatan SVM memiliki performa lebih baik daripada metode Decision Tree. Metode Decision Tree juga memiliki performa yang baik, dengan menggunakan PCA dengan nilai n=5, Decision Tree memiliki akurasi 96.55% yang berada pada perbandingan Split Data 85% : 15%.
Digital Image Encryption Using Logistic Map Muhammad Rizki; Erik Iman Heri Ujianto; Rianto Rianto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.5389

Abstract

This study focuses on the application of the logistic map algorithm in the Python programming language for digital image encryption and decryption. It investigates the impact of image type, image size, and logistic map parameter values on computational speed, memory usage, encryption, and decryption results. Three image sizes (300px 300px, 500px x 500px, and 1024px x 1024px) are considered in TIFF, JPG, and PNG formats. The digital image encryption and Decryption process utilizes the logistic map algorithm implemented in Python. Various parameter values are tested for each image type and size to analyze encryption and decryption outcomes. The findings indicate that the type of image does not affect memory usage, which remains consistent regardless of image type. However, image type significantly influences the decryption results and computation time. In particular, the TIFF image type exhibits the fastest computation time, with durations of 0.17188 seconds, 0.28125 seconds, and 1.10938 seconds for 300px x 300px, 500px x 500px, and 1024px x 1024px images, respectively. In addition, the encryption results vary depending on the type of image. The logistic map algorithm is unable to restore encryption results accurately for JPG images. Furthermore, research highlights that higher values of x, Mu and Chaos lead to narrower histogram values, resulting in improved encryption outcomes. This study contributes to the field by exploring the application of the logistic map algorithm in Python and analyzing the effects of image type, image size, and Logistic Map parameter values on computation time, memory usage, and digital image encryption and Decryption results. Prior research has not extensively addressed these aspects in relation to the Logistic Map algorithm in Python.
Upaya peningkatan kesadaran keamanan data bagi guru Bahasa Inggris SMA di Kabupaten Bantul Rianto, Rianto; Tri Untoro, Iwan Hartadi
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 7, No 3 (2024): Agustus
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v7i3.2106

Abstract

Saat ini, telepon cerdas (smartphone) bukan hanya alat untuk berkomunikasi, tetapi merupakan alat bantu dalam menyelesaikan pekerjaan manusia sehari-hari. Hal ini karena kemajuan teknologi yang berhasil memadukan kecanggihan telekomunikasi dan teknologi informasi dalam satu genggaman. Namun, intensitas penggunaan smartphone yang tinggi ini menimbulkan celah dalam keamanan data dan informasi bagi penggunanya. Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan kesadaran pengguna smartphone dalam keamanan data dan informasi sehingga kejahatan dunia maya dapat diminimalkan. PKM ini termotivasi dari data hasil kuesioner mengenai kesadaran keamanan data dan informasi bagi guru Bahasa Inggris pada Sekolah Menengah Atas (SMA) di kabupaten Bantul. Sebagai tindak lanjut kemudian diadakan Workshop on Digital Literacy: Internet & Mobile Security. Meskipun banyak faktor yang dapat mempengaruhi terjadinya kejahatan dunia maya (cyber-crime), tetapi workshop ini berhasil membekali peserta dengan pengetahuan dasar untuk meminimalkannya.
BRAND TRUST AND CUSTOMER LOYALITY IN SERVICE COMPANIES HEALTH Munawaroh, Emi; Rianto
Jurnal Ekonomi dan Bisnis Airlangga Vol. 32 No. 1 (2022): JURNAL EKONOMI DAN BISNIS AIRLANGGA
Publisher : Fakultas Ekonomi dan Bisnis, Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jeba.V32I12022.93-102

Abstract

Introduction: This study was conducted to examine the effect of trust in brand (brand characteristic, company characteristic, and customer - brand characteristic) on brand loyalty in hospital patients. Methods: The method used in this study is a quantitative descriptive research method with a multiple linear regression analysis approach using 100 respondents who have used the services of RSUD Dr. Sudirman Kebumen. Results: The results of this study indicate that trust in brand has a positive effect on brand loyalty, either partially for each dimension of brand characteristic, company characteristic, and customer-brand characteristic or simultaneously. Furthermore, customer-brand characteristic is the dominant variable even though the difference is not great. Therefore, it can be concluded that, in building brand loyalty, it requires building trust from the brand with characteristics starting from the brand itself, and how the patient's relationship with the brand is established. Conclusion and suggestion The author finds that building brand loyalty in service companies, especially health services at regional companies, requires good brand trust management. This is a new finding because previous research has focused on goods industry. Brand loyalty is focused not only on a tangible product industry, but even health service companies need good brand awareness, especially trust, to be able to maintain customer loyalty to the brand.
Convolutional Neural Network for Identifying Tree Species Using Stem Images Pramesti, Nadia; Rianto, Rianto
Telematika Vol 20 No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.8774

Abstract

Purpose: Identification of tree species based on stem images using programming assistance to design an automation tool to be able to distinguish tree species directly based on stem images from the new data entered.Design/methodology/approach: Identifying tree species is usually done using leaf images, in previous studies related to identifying tree species based on leaf images this resulted in quite high accuracy but was felt to be not optimal. In this study, we used a convolutional neural network to compare the accuracy of bar images.Findings/result: from 1000 tree trunk image data, identification was carried out using the help of python with the CNN method it can be concluded that the test results used the best acuration at epoch 25 with a value reaching 96.80%Originality/value/state of the art: Research with theme identification of tree species based on stem images using the CNN method has never been done by previous researchers. 
Sistem Rekomendasi Hybrid Menggunakan Metode Switching Rizki, Muhammad; Rianto, Rianto
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 2 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i2.6220

Abstract

Technological developments force businesses to provide the best service by making recommendation systems a solution to maintain consumer loyalty. Many studies have been carried out on recommendation systems to overcome Cold-Start or Serendipitous Problems. This study conducted Hybrid Collaborative Filtering and Content-Based filtering using the Switching method as a medium for selecting the correct data and attributes. Furthermore, the data is processed using the TF-IDF and KNN algorithms. This study conducted several tests using various K values and the training and testing data composition. The test results show that the highest accuracy produced by the model that has been developed is 83.62 percent for the switching method with the product category attribute as the variable label and 74.9 percent for the switching method with the rating attribute as the variable label. The training and testing data ratio used in this study is 70:30, with a K equals 3. The study's results also found a significant correlation between the K value and the accuracy value, where a high K value would also result in high accuracy.
Studi Komprehensif Keamanan Siber: Perbandingan Teknologi AI dengan Sistem Non-AI dalam Deteksi dan Pencegahan Ancaman Santika, Yollandaru Yoga; Rianto, Rianto; Ujianto, EIH
Jurnal Komtika (Komputasi dan Informatika) Vol 9 No 1 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v9i1.13149

Abstract

This research examines cybersecurity approaches in Indonesia, focusing on the implementation of Artificial Intelligence (AI) technology compared to non-AI systems in detecting and preventing threats. The study identifies the advantages of AI, such as its capabilities in large-scale data analysis, detection of suspicious patterns, and reduction of human error. The methodology follows PRISMA guidelines for systematic literature review. Findings reveal that while AI can enhance threat detection effectiveness and resilience against attacks, the adoption of this technology in Indonesia remains limited by infrastructure, resources, and technical expertise. This research is expected to provide insights for more proactive national cybersecurity policies and support the development of AI technology in future information security initiatives.
Co-Authors Andri Yudha Pratama Andri Yudha Pratama Anggara, Afwan Apriansyah, Ferryma Arba Arief Hermawan Aziz Perdana Daegal, Andre Demas Risdho Listianto Dewi, Septi Riana Dian Wijayanti Donny Avianto Edi Priyanto EIH Ujianto Eko Setyo Humanika Endang Setyawati Enggar Novianto Enggar Novianto Enny Itje Sela Enny Itje Sela Erik Herman Heri Ujianto Erik IH Ujianto Erik Iman Heri Ujianto Erik Iman Heri Ujianto Erik Iman HU Evada Rustina Fatih Ahmad Zakaria Hening Nakuloadi Ilham Fanani Kristianto Pratama Dessan Putra Meidhika Nawa Sapta Muhammad Rizki Muhammad Rizki Munawaroh, Emi Nadia Pramesti Nur Wening Oktafiani, Rian Paulus Insap Santosa Pramesti, Nadia Ratika Tulus Wahyuhana Retno Prihatini Rian Oktafiani Rian Oktafiani Rubangi Rubangi Santika, Yollandaru Yoga Saputra, Candra Heru Setiafindari, Widya Siska Howay Sulistyo Dwi Sancoko Syafrudin, Teguh Syahab, Alfin Syarifuddin Teguh Widodo Teguh Widodo Tri Untoro, Iwan Hartadi Ujianto, EIH Ujianto, Erik IH Utami, Wahyu Sri Wayan Praka Zuzzaifa, Nur